throw exception on wso2 - exception

I am new to WSO2, and would like an example to throw exception on wso2. Type I have a variable balance and wanted to validate if it is less than zero if it is to run the sequence and send a message. Could someone help me?

There are 2 ways one is makefault mediator , below is the syntax which you can use .
<makefault version="soap11">
<code xmlns:soap11Env="http://schemas.xmlsoap.org/soap/envelope/" value="soap11Env:Client"/>
<reason value="Internal technical error. Please, contact support team"/>
<role>WSO2</role>
<detail expression="$ctx:FaultDetail"/>
</makefault>
Other way is to call an error sequence which you need to define when you are building a sequence

Related

usefulness of tdie with java exceptions inTalend

I want to know what is the usefulness of tdie comparing to Java exceptions in talend knowing that when an exception occur tdie exit the job and is passing the error to tlogcatcher .The same thing can be done by java exceptions (they also can be received by tlogcatcher and they exit the job ).
So why java exceptions are not enough for logging so we use tdie?/what is the limits of java exceptions.
I don't use tDie after a component exception (like Component-->oncomponenterror-->tDie . As you stated, the java exception is caught : if you put a tDie, you'll only have 2 lines logged instead of just one.
I use tDie to put an end to a job if a condition is not met : for example , I can test the number of lines inserted in a DB, if it is 0 , I call tDie to end the job (with tDBOutput--if-->tDie , with a test on number of lines inserted inside the if condition).
This is more like a functional error than a technical one that I want to catch in this case.

kafka-python 1.3.3: KafkaProducer.send with explicit key fails to send message to broker

(Possibly a duplicate of Can't send a keyedMessage to brokers with partitioner.class=kafka.producer.DefaultPartitioner, although the OP of that question didn't mention kafka-python. And anyway, it never got an answer.)
I have a Python program that has been successfully (for many months) sending messages to the Kafka broker, using essentially the following logic:
producer = kafka.KafkaProducer(bootstrap_servers=[some_addr],
retries=3)
...
msg = json.dumps(some_message)
res = producer.send(some_topic, value=msg)
Recently, I tried to upgrade it to send messages to different partitions based on a definite key value extracted from the message:
producer = kafka.KafkaProducer(bootstrap_servers=[some_addr],
key_serializer=str.encode,
retries=3)
...
try:
key = some_message[0]
except:
key = None
msg = json.dumps(some_message)
res = producer.send(some_topic, value=msg, key=key)
However, with this code, no messages ever make it out of the program to the broker. I've verified that the key value extracted from some_message is always a valid string. Presumably I don't need to define my own partitioner, since, according to the documentation:
The default partitioner implementation hashes each non-None key using the same murmur2 algorithm as the java client so that messages with the same key are assigned to the same partition.
Furthermore, with the new code, when I try to determine what happened to my send by calling res.get (to obtain a kafka.FutureRecordMetadata), that call throws a TypeError exception with the message descriptor 'encode' requires a 'str' object but received a 'unicode'.
(As a side question, I'm not exactly sure what I'd do with the FutureRecordMetadata if I were actually able to get it. Based on the kafka-python source code, I assume I'd want to call either its succeeded or its failed method, but the documentation is silent on the point. The documentation does say that the return value of send "resolves to" RecordMetadata, but I haven't been able to figure out, from either the documentation or the code, what "resolves to" means in this context.)
Anyway: I can't be the only person using kafka-python 1.3.3 who's ever tried to send messages with a partitioning key, and I have not seen anything on teh Intertubes describing a similar problem (except for the SO question I referenced at the top of this post).
I'm certainly willing to believe that I'm doing something wrong, but I have no idea what that might be. Is there some additional parameter I need to supply to the KafkaProducer constructor?
The fundamental problem turned out to be that my key value was a unicode, even though I was quite convinced that it was a str. Hence the selection of str.encode for my key_serializer was inappropriate, and was what led to the exception from res.get. Omitting the key_serializer and calling key.encode('utf-8') was enough to get my messages published, and partitioned as expected.
A large contributor to the obscurity of this problem (for me) was that the kafka-python 1.3.3 documentation does not go into any detail on what a FutureRecordMetadata really is, nor what one should expect in the way of exceptions its get method can raise. The sole usage example in the documentation:
# Asynchronous by default
future = producer.send('my-topic', b'raw_bytes')
# Block for 'synchronous' sends
try:
record_metadata = future.get(timeout=10)
except KafkaError:
# Decide what to do if produce request failed...
log.exception()
pass
suggests that the only kind of exception it will raise is KafkaError, which is not true. In fact, get can and will (re-)raise any exception that the asynchronous publishing mechanism encountered in trying to get the message out the door.
I also faced the same error. Once I added json.dumps while sending the key, it worked.
producer.send(topic="first_topic", key=json.dumps(key)
.encode('utf-8'), value=json.dumps(msg)
.encode('utf-8'))
.add_callback(on_send_success).add_errback(on_send_error)

How can I throw an exception in Matlab?

I am writing some code and for now I am making some functions, but I'm not writing them yet. I'm just making an empty function that will do nothing yet. What I would like to do is throw an exception if the function is run, to prevent me from forgetting writing the function.
The easiest way is:
error('Some useful error message.')
Matlab is happier is you assign an identifer to you error message, like this:
error('toolsetname:other_identifying_information','Some useful error message here.')
The identifying information is reported with some of the error handling routines, for example, try running lasterror after each of the above calls.
You can also use:
throw(MException('Id:id','message'));
There is a nice feature to MException, it can be used as sprintf:
throw(MException('Foo:FatalError',...
'First argument of Foo is %s, but it must be double',class(varargin{1}) ));
As commented correctly by #edric, this sprintf functionality can be a double edged sword. If you use some of the escape characters, it might behave not like you want it.
throw(MException('Foo:FatalError',...
'I just want to add a \t, no tab!' ));
Did you read the MATLAB documentation for "Throwing an exception"?

What are the cons of returning an Exception instance instead of raising it in Python?

I have been doing some work with python-couchdb and desktopcouch. In one of the patches I submitted I wrapped the db.update function from couchdb. For anyone that is not familiar with python-couchdb the function is the following:
def update(self, documents, **options):
"""Perform a bulk update or insertion of the given documents using a
single HTTP request.
>>> server = Server('http://localhost:5984/')
>>> db = server.create('python-tests')
>>> for doc in db.update([
... Document(type='Person', name='John Doe'),
... Document(type='Person', name='Mary Jane'),
... Document(type='City', name='Gotham City')
... ]):
... print repr(doc) #doctest: +ELLIPSIS
(True, '...', '...')
(True, '...', '...')
(True, '...', '...')
>>> del server['python-tests']
The return value of this method is a list containing a tuple for every
element in the `documents` sequence. Each tuple is of the form
``(success, docid, rev_or_exc)``, where ``success`` is a boolean
indicating whether the update succeeded, ``docid`` is the ID of the
document, and ``rev_or_exc`` is either the new document revision, or
an exception instance (e.g. `ResourceConflict`) if the update failed.
If an object in the documents list is not a dictionary, this method
looks for an ``items()`` method that can be used to convert the object
to a dictionary. Effectively this means you can also use this method
with `schema.Document` objects.
:param documents: a sequence of dictionaries or `Document` objects, or
objects providing a ``items()`` method that can be
used to convert them to a dictionary
:return: an iterable over the resulting documents
:rtype: ``list``
:since: version 0.2
"""
As you can see, this function does not raise the exceptions that have been raised by the couchdb server but it rather returns them in a tuple with the id of the document that we wanted to update.
One of the reviewers went to #python on irc to ask about the matter. In #python they recommended to use sentinel values rather than exceptions. As you can imaging just an approach is not practical since there are lots of possible exceptions that can be received. My questions is, what are the cons of using Exceptions over sentinel values besides that using exceptions is uglier?
I think it is ok to return the exceptions in this case, because some parts of the update function may succeed and some may fail. When you raise the exception, the API user has no control over what succeeded already.
Raising an Exception is a notification that something that was expected to work did not work. It breaks the program flow, and should only be done if whatever is going on now is flawed in a way that the program doesn't know how to handle.
But sometimes you want to raise a little error flag without breaking program flow. You can do this by returning special values, and these values can very well be exceptions.
Python does this internally in one case. When you compare two values like foo < bar, the actual call is foo.__lt__(bar). If this method raises an exception, program flow will be broken, as expected. But if it returns NotImplemented, Python will then try bar.__ge__(foo) instead. So in this case returning the exception rather than raising it is used to flag that it didn't work, but in an expected way.
It's really the difference between an expected error and an unexpected one, IMO.
exceptions intended to be raised. It helps with debugging, handling causes of the errors and it's clear and well-established practise of other developers.
I think looking at the interface of the programme, it's not clear what am I supposed to do with returned exception. raise it? from outside of the chain that actually caused it? it seems a bit convoluted.
I'd suggest, returning docid, new_rev_doc tuple on success and propagating/raising exception as it is. Your approach duplicates success and type of 3rd returned value too.
Exceptions cause the normal program flow to break; then exceptions go up the call stack until they're intercept, or they may reach the top if they aren't. Hence they're employed to mark a really special condition that should be handled by the caller. Raising an exception is useful since the program won't continue if a necessary condition has not been met.
In languages that don't support exceptions (like C) you're often forced to check return values of functions to verify everything went on correctly; otherwise the program may misbehave.
By the way the update() is a bit different:
it takes multiple arguments; some may fail, some may succeed, hence it needs a way to communicate results for each arg.
a previous failure has no relation with operations coming next, e.g. it is not a permanent error
In that situation raising an exception would NOT be usueful in an API. On the other hand, if the connection to the db drops while executing the query, then an exception is the way to go (since it's a permament error and would impact all operations coming next).
By the way if your business logic requires all operations to complete successfully and you don't know what to do when an update fails (i.e. your design says it should never happen), feel free to raise an exception in your own code.

How do I find character positions in ANTLR 2?

I have a simple grammar, and have produced a pair of c# classes using antlr 2.7.7. When the parser finds an error with a token, it throws an exception; I want to find out how many characters into a parsed stream the token came. How do I do that?
It's been a long time ago since I played with ANTLR, but if I remember well, to do what you want, I had to subclass the parser to keep a counter of characters that was incremented each time a new token was found (with the token length of course).
You ought to read chapter 10 ("Error Reporting and Recovery") from Terrence Parr's book "The Definitive ANTLR Reference".
Not knowing what target language you're using, it'll be hard to tell you exactly what to do. But I'll assume you're using the Java target, and you can correct me if I'm wrong.
When an ANTLR recognizer fails to match an input string, it throws a very specific exception, based on the failure context. (There are nine different kinds of exceptions, RecognitionException is the root type, and it has eight subclasses of its own: MismatchedTokenException, MismatchedTreeNodeException, NoViableAltException, EarlyExitException, FailedPredicateException, MismatchedRangeException, MismatchedSetException, MismatchedNotSetException).
The root exception type (RecognitionException) has a few handy public fields that you might want to take a look at (specifically: "index", "line" and "charPositionInLine"). The "index" field tells you the exact character position where the error was found. The "line" and "charPositionInLine" fields are pretty self-explanatory. Here's the JavaDoc:
http://www.antlr.org/api/Java/classorg_1_1antlr_1_1runtime_1_1_recognition_exception.html